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• W4376611512 abstract "The quantitative logs method is designed for objective facies analysis of thick sedimentary successions. This method enables the analysis of whole successions instead of selected intervals arbitrarily considered as representative and results in a database suitable for further analysis, e.g., statistical, quantitative stratigraphy, or facies modelling. The logging procedure involves the following steps: (i) each of the logged sedimentary features is classified according to a standard, e.g., grain-size follows the phi scale or Wentworth classes are applied for bed thickness; (ii) in the course of logging, the whole succession is subdivided into intervals, each of which is characterised by a predominant (i.e., modal) class of the considered feature; (iii) such modal class characterises a part of the section that has a specific thickness and is called a ‘modally homogeneous interval’ (MHI); and (iv) the lower and upper boundary of each MHI are defined by a change in the modal class. The thickness of all MHIs characterised by the same class interval is then added. The grand total of such component sub-totals for all class intervals of the logged feature equals the log thickness and is the basis for the calculation of frequency distribution, which characterises the succession from the viewpoint of this feature. Each bar of the resulting histogram represents the percentage of the whole section composed of the strata among which the given class occurs as the modal (i.e., predominant) feature. The method of modal quantitative logs is illustrated here with an example of statistical analysis of selected sections of the Krosno Beds (Oligocene) turbidite succession from the Western Outer Carpathians of Poland." @default.
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• W4376611512 date "2023-05-14" @default.
• W4376611512 modified "2023-10-01" @default.
• W4376611512 title "Modal Quantitative Logs for the Objective Recording and Analysis of Very Thick Sedimentary Sequences" @default.
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• W4376611512 doi "https://doi.org/10.3390/min13050675" @default.
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